Predicting Criterion Scores & Simple Linear Regression

In this video, I explain how regression coefficient estimates from a simple linear regression model can be used to predict criterion scores. This video is meant to provide a foundation for understanding how, in an employee selection context, organizations can (a) estimate a linear regression model based on data from a validation study sample for a selection tool (e.g., personality test) and a criterion (e.g., job performance), (b) construct an equation to based on the model coefficient estimates based on that validation sample data, and (c) apply the equation to future applicant scores on the selection tool in order to predict their criterion scores. This approach can be extended for multi-tool selection systems (i.e., selection systems with 2+ selection tools) by estimating a multiple linear regression model and applying what is referred to as a compensatory approach to making employee selection decisions.
To learn more about simple linear regression at a conceptual level, check out: • Simple Linear Regression
To learn how to use R to estimate a simple linear regression, including evaluating whether statistical assumptions have been met, check out: • Simple Linear Regressi...
To learn how to use R to estimate a simple linear regression model in order to predict criterion scores, check out: • Predicting Criterion S...
To learn how to use R to a estimate a multiple linear regression, including evaluating whether statistical assumptions have been met, check out: • Multiple Linear Regres...
To learn how to use R to a estimate a multiple linear regression, with an emphasis on interpreting incremental validity, check out: • Evaluating Incremental...
To learn how to use R to estimate a multiple linear regression model in order to predict criterion scores, which is part of applying a compensatory approach to making selection decisions, check out: • Applying a Compensator...